Social media messages may be monitored to determine trends and identify issues that may be arising. A keyword, hash tag, or phrase of interest may be found in messages a number of times and examined over time. In such a manner, the popularity of a particular issue within a community of users may be determined.
Clustering is a method used to group a set of related items where the items in the cluster are more closely related to each other than to items in other clusters. Cluster analysis is typically used in data mining. Comments on social media are expected when an event occurs, and data analysis can be very useful.
A large scale event like a natural disaster typically creates a large and related set of social media comments. A significantly delayed flight may create a similar, but smaller set of comments. Each of these sets of comments represents a cluster. Within sets of comments, or clusters, there is typically an average nominative value and the cluster develops in a certain way. A known cluster or trend gives expected results that are typical and predictable.